Patrick Vega
About Patrick Vega
Patrick Vega is a Postdoctoral Researcher at Inria in Sophia Antipolis, France, specializing in efficient photovoltaic cells and error estimators for Maxwell's equations. He has held various academic positions at multiple universities in Chile and earned his Doctorate in Applied Sciences with a focus on Mathematical Engineering from Universidad de Concepción.
Work at Inria
Patrick Vega has been working at Inria as a Postdoctoral Researcher since 2019. His research is conducted in Sophia Antipolis, France, where he focuses on advanced mathematical modeling and computational techniques. His contributions include the development of efficient photovoltaic cells, which are essential for sustainable energy solutions. Vega's role at Inria involves collaboration with other researchers and institutions, enhancing the impact of his work in the field of applied sciences.
Education and Expertise
Patrick Vega studied at Universidad de Concepción, where he earned a Doctor en Ciencias Aplicadas con mención en Ingeniería Matemática from 2014 to 2018. Prior to his doctoral studies, he completed his undergraduate degree in Ingeniero Civil Matemático at the same institution from 2008 to 2014. His educational background provides a strong foundation in applied mathematics and engineering, which informs his current research endeavors.
Background
Before joining Inria, Patrick Vega held several academic positions at various institutions. He worked as an Académico Jornada Parcial at Universidad de Concepción in multiple capacities from 2012 to 2016, accumulating experience over several years. Additionally, he worked at Universidad Católica de la Santísima Concepción and Universidad Andrés Bello in similar roles. His diverse teaching experience complements his research activities.
Research Contributions
Patrick Vega's research primarily focuses on deriving, analyzing, and implementing a posteriori error estimators for HDG discretizations of Maxwell's equations. He emphasizes validating his research through realistic benchmarks, particularly in wave propagation problems. His work aims to enhance the accuracy and efficiency of computational methods in applied mathematics, contributing to advancements in the field.